MODIStsp

We are happy to report that our MODIStsp package for automatic preprocessing of MODIS time series has been recently approved for being included in the rOpenSci ecosystem of R packages for reproducible science!
We wish to thank reviewers Leah Wasser and Jeffrey Hanson for providing really valuable insights during the onboarding review process. We think their contribution really helped in improving the package!
Please also note that MODIStsp website was also migrated, and is now available at http://ropensci.

We are happy to report that a new version of MODIStsp (1.3.4) is on CRAN as of today !
The new version introduces a strongly improved GUI (thanks mainly to @lwasser comments in her review for MODIStsp onboarding on ropensci). The new GUI facilitates the selection of layers to be processed, and allows interactive selection of the processing spatial extent over a map (thanks to @timsalabim and @timelyportfolio for implementing some changes on mapview to allow this!

A new version of MODIStsp (1.3.3) is on CRAN as of today ! Below, you can find a short description of the main improvements.
Processing speed improvements Processing of MODIS layers after download (i.e., scale and offset calibration, computation of Spectral Indexes and Quality Indicators) is now much faster.
As you can see in the figure, processing time was almost halved on my (not so fast) laptop. This was achieved by modifying all computation functions so to use raster::calc() and raster::overlay() (more on this in a later post).

As promised in my last post, here is a short guide with some tips and tricks for building a documentation website for an R package using pkgdown.
In the end, this guide ended up way longer than I was expecting, but I hope you’ll find it useful, although it often replicates information already available in pkgdown documentation !
Prerequisites To build a website using pkgdown, all you need to have is an R package hosted on Git Hub, with a file structure “tweaked” with some functionality provided by devtools.

The MODIStsp website, which lay abandoned since several months on github pages, recently underwent a major overhaul thanks to pkgdown. The new site is now available at http://ropensci.github.io/MODIStsp/
We hope that the revised website will allow to navigate MODIStsp-related material much more easily than either github or the standard CRAN documentation, and will therefore help users in better and more easily exploiting MODIStsp functionality.
The restyling was possible thanks to the very nice “pkgdown” R package (http://hadley.

We are glad to report that MODIStsp is now also available on CRAN ! From now on, you can therefore install it by simply using:
install.packages("MODIStsp")
In v 1.3.2 we also added the functionality to automatically apply scale and offset coefficients on MODIS original values according with the specifications of single MODIS products. Setting the new “Scale output values” option to “Yes”, scale factors and offsets are applied (if existing).

MODIStsp is a R package allowing automatic download and preprocessing of MODIS Land Products time series, available at this https://github.com/ropensci/MODIStsp github page (See also here for additional information)
v1.3.1 adds functionality for processing MODIS snow cover products, accelerated download, processing specified portions of years, plus various bug fixing and improvements.
MODIStsp: the main processing GUI
See here for a detailed description of introduced changes
We hope you will find the new version useful and that we didn’t introduce too many bugs !

MODIStsp v1.3.0 has been finally released !
It adds the much-needed functionality for downloading and preprocessing MODIS Collection 006 datasets. Off-line preprocessing of already downloaded hdf images was also improved, and the GUI was a bit revamped to improve user-friendliness (A detailed changelog can be found here).
More detailed usage instructions were also added to the main github page, and a FAQ section addressing common issues with the package (e.g., installation problems, etc) was added.